FLEXIBILITY ANALYSIS OF A FOOD PROCESSING INDUSTRY

Authors

  • J. R. Khan NFC Institute of Engineering and Fertilizer Research, Faisalabad, Pakistan
  • W. Rehman COMSATS Institute of Information Technology, Lahore, Pakistan
  • M. S. Tahir Department of Chemical Engineering and Environmental Technology, Graz University of Technology, Austria

Abstract

In this article, the flexibility analysis of a food processing industry (sugar) is carried out. The system is analysed under different operating conditions and its effect on output quality examined. If the overall system, design and operation, did not achieve the specific product quality (of sugar); the design was rendered as incompetent to achieve this objective. However, for certain regions of its operation, the design was able to meet the quality criteria as desired; in which case it was found to be in approach of the objective. Based upon this characterization, those values of feasible region were found where product specification could be achieved by the design. This region was then explored further to find optimum value of flexibility that can be achieved in case of variation in feed composition. The paper can be looked as a starting work in applying flexibility analysis approach to complex food processes where environmental uncertainties are common; such as in multi-purpose multi-product plants. When coupled with a suitable control, this technique can help to achieve optimum profit advantages to any batch industry. Monte Carlo Simulation is carried out to explore different regions of feasible operation and increase flexibility from 0.00865 to 0.08686 (an order of 10). This technique has helped to quantify flexibility and improve regions of feasible operation of a sugary industry and increase its profitability. This approach can be used to other food processing, pharmaceutical and batch type industries.

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Published

29-06-2020

How to Cite

[1]
J. R. Khan, W. Rehman, and M. S. Tahir, “FLEXIBILITY ANALYSIS OF A FOOD PROCESSING INDUSTRY”, The Nucleus, vol. 46, no. 3, pp. 311–320, Jun. 2020.

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Articles